Congestion Model Research Articles

Traffic Congestion Modeling and Impact on the Work Environment at Brawijaya University

Traffic Congestion Modeling and Impact on the Work Environment at Brawijaya University

Branching in flow networks with linear congestion

In our modern world, we rely on the proper functioning of a variety of networks with complex dynamics. Many of them are prone to congestion due to high loads, which determines their operation and resilience to failures. In this article, we propose a fundamental model of congestion where travel times increase linearly with the load. We show that this model interpolates between shortest path and Ohmic flow dynamics, which both have a broad range of applications. We formulate the model as a quadratic programme and derive a generalization of Ohm's law, where the flow of every link is determined by a potential gradient in a nonlinear way. We provide analytic solutions for fundamental network topologies that elucidate the transition from localized flow to a branched flow. Furthermore, we discuss how to solve the model efficiently for large networks and investigate the resilience to structural damages.

Models of HF Interference over Cyprus

Interference from other users, due to the long-distance propagation of HF signals, causes spectral congestion, which is considered a primary detrimental effect on HF (3–30 MHz) communication systems. More than a year of HF electric field measurements from a calibrated monopole HF antenna collected by a dedicated measurement system installed in Cyprus have been used to compare neural networks and non-linear regression for the development of single-allocation congestion models in the HF spectrum. These models can be used to advise operators on typical interference spectral congestion levels and assist in the planning and management of frequency usage by assessing the interference level to alleviate spectral congestion in the HF band over Cyprus. The performance of these alternative modeling approaches is discussed in the context of their ability to successfully capture the diurnal variability of HF interference at a certain incident field strength threshold.

Cutaneous Microcirculatory Flow Sensing for Flap Monitoring in a Porcine Model of Arterial and Venous Occlusion

PURPOSE: Cutaneous devices employing near infrared spectroscopy (NIRS) for continuous free flap tissue oxygenation (StO2) monitoring have several limitations. Confounding factors like skin pigmentation and thickness, ambient light incursion, and inconsistency at the skin-sensor interface can alter StO2 measurements. As an alternative means for peripheral free flap monitoring, we present a novel probe that calculates microvascular blood flow velocity by measuring tissue thermal diffusion. This device is cutaneous, wireless and not subject to the same confounding variables as NIRS. METHOD: The cutaneous perfusion sensor includes 5 thermistors, a Bluetooth chip, and small battery mounted on circuit board. A thermal actuator (4-mm diameter) delivers a small amount of thermal power to the surface of the skin. The device is cutaneously mounted with a silicone acrylate adhesive onto target tissue. The diffusion of heat is measured and analytically converted into a measurement of microcirculatory blood flow velocity. Rapid thermal diffusion occurs in situations of high tissue perfusion, while slower thermal diffusion indicates slower or absent near-surface blood flow. This device was tested alongside Vioptix T.Ox in a porcine rectus abdominus myocutaneous flap model of arterial and venous pedicle occlusion. After flap elevation, the flow device and T.Ox were applied to the skin. Acland clamps were alternately applied to the flap artery and veins to achieve conditions of flap ischemia and congestion, each lasting 15 minutes, with a 15 minute intervening recovery period. In total, 10 devices were tested on 16 flaps in 10 separate pigs over 60 unique vaso-occlusive events. RESULTS: Continuous monitoring was accomplished and no connection loss was observed with either T.Ox or the novel devices. Flow measurements were responsive to both ischemia and congestion, and returned to baseline during recovery periods. Flow measurements corresponded with vascular occlusion and release, and closely followed StO2. Cross-correlation at zero lag showed agreement between these two sensing modalities, ranging from 0.76 to 0.83. Two novel devices tested simultaneously on the same flap showed only minor variations in flow measurements, with a cross-correlation of 0.87. CONCLUSION: This novel probe is capable of detecting changes in tissue microcirculatory blood flow. This device performed well in a swine model of flap ischemia and congestion, and shows promise as a potentially useful clinical tool. Because flow measurements are not affected by the variable lighting and light absorbing properties of tissue, this monitoring strategy has the potential to provide more consistent information than NIRS. Future studies will characterize longevity of the device over a period of several days.

Hybrid Scheduling Model Based on Fare Incentives for Peak Time Interval of the Metro: The Harbin Metro System

Considering the operation efficiency of the metro system, the boarding queuing problem is a complex and intractable dilemma caused by the security and ticket checking process in urban metro stations, especially for the mass-transit metro system in China. In this study, a novel scheme of fare differentials based on demand control and congestion management for reducing congestion in the metro boarding process was proposed. In addition, we extended Vickrey’s point-queue model into a boarding congestion model incorporating the bidesired departure time considering the security and ticket checking process in stations as a continuum bottleneck. The train-run and departure time choosing behaviors of passengers under different schedule gaps of the adjacent train runs are explored when the boarding system achieves user equilibrium in the proposed model. Then, we examined the demand regulatory mechanisms of fare incentives (fare differentials) in reducing the queuing boarding time in metro stations when the optimization of the schedule gaps is ineffective in the pattern of mass-scale travel demand. The analytical solutions of these two optimal methods (schedule gaps and fare differentials) for boarding congestion management are presented. After comparing the two congestion-reduced methods, the fare incentive rule has a better regulation effect on the smoothing of travel demand. The results of the sensitivity analysis using numerical simulations reveal the regulatory mechanism of fare differentials in reducing the queuing time and increasing the incremental revenue. (1) The demand threshold is only related to the boarding capacity and schedule gaps (i.e., the greater the boarding capacity and schedule gaps, the greater the passenger capacity of the metro station). (2) The effect of fare incentives in reducing the boarding congestion is better if the lower fare is implemented in the later train runs. (3) A lower fare differential between two adjacent metro runs can be used to regulate the proportion of staggered passengers in the queuing line to reduce the crowd gathering in the metro station hall when travel demand is high, meanwhile, a higher fare differential between two adjacent metro shuttles can increase incremental revenue effectively. (4) The measure of fare differentials causes worse results in both the reduction of the queuing time and the increase of the incremental revenue when the metro travel demand is lower than the demand threshold. This conclusion is consistent with the pattern of reality and experience. Therefore, the definition and judgment conditions of demand thresholds, introduced in this study, can provide theoretical guidance when implementing fare incentive policies in aviation and metro networks.

Vortex vein congestion in the monkey eye: A possible animal model of pachychoroid.

To create vortex vein congestion in the monkey eye as a possible pachychoroid model. We ligated superotemporal and inferotemporal vortex veins at the surface of the sclera in monkey eyes. Optical coherence tomography (OCT) and indocyanine green angiography (ICGA) were performed before and 2, 7, and 28 days after the vortex vein ligations to investigate changes in vortex vein morphology and alterations in choroidal blood flow. Before the vortex vein ligations, en face OCT and ICGA images showed well organized vortex veins as well as horizontal and vertical watershed zones. Two days after the vortex vein ligations, dilatation of the superotemporal and inferotemporal vortex veins as well as intervortex venous anastomoses were seen on en face OCT and ICGA images. B-mode OCT images showed choroidal thickening associated with dilatation of the outer choroidal vessels. Moreover, video ICGA revealed choriocapillaris filling delay and pulsatile flow in the dilated vortex veins. At 7 and 28 days after we ligated the vortex veins, these findings were reduced, except for the intervortex venous anastomoses. We created a monkey model of vortex vein congestion by ligating two vortex veins. This animal model demonstrated pachychoroid-related findings, indicating that vortex vein congestion is involved in the pathogenesis of pachychoroid. However, remodeling of the choroidal drainage route via intervortex venous anastomosis appeared to compensate for the vortex vein congestion created in this model.

Social optimum for linear staggered shifts in a single-entry traffic corridor with no late arrivals

The staggered shifts scheme has been widely discussed to alleviate traffic congestion in recent years. However, most previous research considers limited numbers of work start times and ignores the dynamic characteristics of traffic flow. In this paper, we consider a linear staggered shifts (LSS) scheme, which assumes the work start times for commuters is a continuous time period, to replace the identical work start time in a single-entry traffic corridor. We analytically derive the social optimal (SO) assignment and find the optimal LSS scheme in the flow congestion model with no late arrivals. The evolvement laws of traffic flow in the time–space dimension and corresponding economic properties with the optimal LSS scheme are also investigated. Results demonstrate that the application of the proposed optimal LSS scheme will not change the flow pattern of commuters in SO but significantly reduce the total trip cost.

Inhibition of platelet-derived growth factor pathway suppresses tubulointerstitial injury in renal congestion.

Objective:Increased central venous pressure in congestive heart failure is responsible for renal dysfunction, which is mediated by renal venous congestion. Pericyte detachment from capillaries after renal congestion might trigger renal fibrogenesis via pericyte-myofibroblast transition (PMT). Platelet-derived growth factor receptors (PDGFRs), which are PMT indicators, were upregulated in our recently established renal congestion model. This study was designed to determine whether inhibition of the PDGFR pathway could suppress tubulointerstitial injury after renal congestion.Methods:The inferior vena cava between the renal veins was ligated in male Sprague-Dawley rats, inducing congestion only in the left kidney. Imatinib mesylate or vehicle were injected intraperitoneally daily from 1 day before the operation. Three days after the surgery, the effect of imatinib was assessed by physiological, morphological and molecular methods. The inhibition of PDGFRs against transforming growth factor-β1 (TGFB1)-induced fibrosis was also tested in human pericyte cell culture.Results:Increased kidney weight and renal fibrosis were observed in the congested kidneys. Upstream inferior vena cava (IVC) pressure immediately increased to around 20 mmHg after IVC ligation in both the imatinib and saline groups. Although vasa recta dilatation and pericyte detachment under renal congestion were maintained, imatinib ameliorated the increased kidney weight and suppressed renal fibrosis around the vasa recta. TGFB1-induced elevation of fibrosis markers in human pericytes was suppressed by PDGFR inhibitors at the transcriptional level.Conclusion:The activation of the PDGFR pathway after renal congestion was responsible for renal congestion-induced fibrosis. This mechanism could be a candidate therapeutic target for renoprotection against renal congestion-induced tubulointerstitial injury.

Intramuscular Microvascular Flow Sensing for Flap Monitoring in a Porcine Model of Arterial and Venous Occlusion.

Commercially available near infrared spectroscopy devices for continuous free flap tissue oxygenation (StO2) monitoring can only be used on flaps with a cutaneous component. Additionally, differences in skin quality and pigmentation may alter StO2 measurements. Here, we present a novel implantable heat convection probe that measures microvascular blood flow for peripheral monitoring of free flaps, and is not subject to the same issues that limit the clinical utility of near-infrared spectroscopy. The intratissue microvascular flow-sensing device includes a resistive heater, 4 thermistors, a small battery, and a Bluetooth chip, which allows connection to a smart device. Convection of applied heat is measured and mathematically transformed into a measurement of blood flow velocity. This was tested alongside Vioptix T.Ox in a porcine rectus abdominis myocutaneous flap model of arterial and venous occlusion. After flap elevation, the thermal device was deployed intramuscularly, and the cutaneous T.Ox device was applied. Acland clamps were alternately applied to the flap artery and veins to achieve 15 minutes periods of flap ischemia and congestion with a 15 minutes intervening recovery period. In total, five devices were tested in three flaps in three separate pigs over 16 vaso-occlusive events. Flow measurements were responsive to both ischemia and congestion, and returned to baseline during recovery periods. Flow measurements corresponded closely with measured StO2. Cross-correlation at zero lag showed agreement between these two sensing modalities. Two novel devices tested simultaneously on the same flap showed only minor variations in flow measurements. This novel probe is capable of detecting changes in tissue microcirculatory blood flow. This device performed well in a swine model of flap ischemia and congestion, and shows promise as a potentially useful clinical tool. Future studies will investigate performance in fasciocutaneous flaps and characterize longevity of the device over a period of several days.

Microsimulation Modeling of Traffic Congestion at Signal Intersection of Thirumangalam Chennai Metrocity

Background: Generally, Chennai is a hub of traffic congestion, where the major roads of the city are filled with vehicle. It gives the challenging situation to the road and traffic management officials to control and regulate the existing traffic with the existing facilities. Objectives: This paper deals with the microscopic simulation of existing road network model which helps in evaluating the performance of the Thirumangalam road intersection such as delay, queue length and also to evaluate and understand the pedestrian vehicle interaction at the intersection and to propose the improvements of signalized intersection in Thirumangalam at Chennai which is without basic facilities like pedestrian crossing time and it causes heavy congestion during peak hour which makes the management to operate the signals manually. Methods/Findings: PTV VISSIM software is used for evaluation and validation of the road network in order to choose the best alternative and optimization measures before implementation. This study helps to improve the existing junction by suggesting the improvement proposals by referring Indian road congress codes (IRC 106, 86, 103) and it also gives the new optimized signal design which is automated to regulate the traffic. Keywords: Signalized Intersections; Signal Design; Microscopic Simulation; Junction Improvements

A spatial decision-making model of smart transportation and urban planning based on coupling principle and Internet of Things

To improve the effect of smart transportation planning in the decision-making process of urban planning space, this paper analyzes the coupling of the smart transportation process. Moreover, this paper analyzes the signal influencing factors of the communication process of smart traffic information based on the Internet of Things, and combines sensor analysis technology to improve the transmission effect of smart traffic signals based on the Internet of Things. Furthermore, this paper proposes a spatial decision-making model of smart transportation and urban planning based on the coupling principle and proposes the establishment and update rules of the road network congestion model, as well as the cluster queuing communication between vehicles. Finally, this paper presents a congestion notification method and a road diversion scheme based on vehicle queues. The experimental study shows that the smart transportation and urban planning spatial decision model based on the coupling principle proposed in this paper has a good effect.

Measures for Airlines to Reduce Airport Congestion Fees: Scheme Design and Performance Assessment

Congestion at busy airports has become one of the major bottlenecks to air transportation development around the world. Airport congestion pricing is one of the most popular market-based mechanisms to relieve airport congestion. This study develops a steady-state congestion model, which considers the market power of airlines and the costs of externalities (i.e., airlines, passengers, and the environment), to estimate congestion fees for different times and queue lengths. To reduce airport congestion fees, we propose and discuss two different options for airlines: schedule adjustment and flight merging in detail from the views of economic, operational, and environmental benefits, and provide a comparative performance analysis of two different measures using an empirical example of Guangzhou Baiyun International Airport (CAN). Our analysis shows that: (1) during the peak period, the congestion fees for one specific flight (operated by B738) may exceed 10,000 RMB, even reach 25,000 RMB; (2) both the methods can relieve congestion and effectively reduce congestion fees; (3) in the CAN case, flight merging by a bigger aircraft B744 is more effective in congestion relief, total fees reduction, and emission mitigation; and (4) schedule adjustment has a better performance of reducing fees per adjusted flight and is more simple and straightforward. We also provide several recommendations to relieve congestion and cut congestion fees.

Uncovering the spatiotemporal patterns of traffic congestion from large-scale trajectory data: A complex network approach

Understanding the spatiotemporal characteristics of traffic congestion is the cornerstone of generating traffic management and control strategies. Based on the large-scale taxi trajectory data in Shenzhen, China, this study designs an effective framework to explore the spatiotemporal patterns of traffic congestions. To bridge trajectory data with urban road networks, we develop a two-stage map-matching method from the aspects of distance and angle. Then, the free-flow speed of each road segment is extracted and employed to identify traffic congestion. In this way, a novel complex network method, named chronological network (chronnet), is utilized for traffic congestion modeling, and we employ an overlapping community detection algorithm to identify region-level bottlenecks. According to the network properties, we explore the influence scope of traffic congestions and uncover the role of each road segment in the propagation process. Meanwhile, community detection results indicate that there are typical local clustering structures in traffic congestions, and each community also has its unique traffic characteristics. Overall, these findings reveal that the complex network can effectively mine the consecutive patterns of traffic congestion.

Modeling and Simulation of Traffic Congestion for Mixed Traffic Flow with Connected Automated Vehicles: A Cell Transmission Model Approach

Connected automated vehicles (CAVs) can significantly shorten the headway of car following, thereby effectively improving the traffic capacity and injecting new power to alleviate traffic congestion. To investigate the congestion characteristics of mixed traffic flow with CAVs and human-driven vehicles (HDVs), this paper proposes a cell transmission model to capture and simulate traffic congestion for mixed traffic flow. Firstly, the Newell, adaptive cruise control (ACC), and cooperative adaptive cruise control (CACC) models are adopted to capture the car-following behavior of different vehicles. Secondly, the fundamental diagram under different penetration rates of CAVs is derived based on car-following models. Then, the cell transmission model (CTM) of mixed traffic flow is developed based on the classical CTM and fundamental diagram of mixed traffic flow. Finally, two simulation methods, mixed traffic flow CTM and micro-simulation, are designed to verify the effectiveness of the proposed model. Moreover, taking the moving bottleneck on the expressway as an example, the congestion characteristics of mixed traffic flow are analyzed using multiple indexes, such as average travel speed, congestion delay, and congestion scale. The results show the following: (i) CAVs can significantly alleviate traffic congestion, (ii) the duration of the bottleneck is positively correlated with the degree of traffic congestion, and (iii) The traffic congestion assessment results under different model parameters slightly differ, but the impact is negligible.

Car following with an inertia-oriented driving technique: A driving simulator experiment

BackgroundFor many decades, car-following (CF) and congestion models have assumed a basic invariance: drivers’ default driving strategy is to keep the safety distance. The present study questions that Driving to keep Distance (DD) is a traffic invariance and, therefore, that the difference between the time required to accelerate versus decelerate must necessarily determine the observed patterns of traffic oscillations. Previous studies have shown that drivers can adopt alternative CF strategies like Driving to keep Inertia (DI) by following basic instructions. The present work aims to test the effectiveness of a DI course that integrates 4 tutorials and 4 practice sessions in a standard PC computer designed to learn more adaptive driving behaviors in dense traffic. Methods. Sixty-eight drivers were invited to follow a leading car that varied its speed on a driving simulator, then they took a DI course on a PC computer, and finally they followed a fluctuating leader again on the driving simulator. The study adopted a pretest-intervention-posttest design with a control group. The experimental group took the full DI course (tutorials and then simulator practice). The control group had access to the DI simulator but not to the tutorials. Results. All participating drivers adopted DD as the default CF mode on the pre-test, yielding very similar results. But after taking the full DI course, the experimental group showed significantly less accelerations, decelerations, and speed variability than the control group, and required greater CF distance, that was dynamically adjusted, spending less fuel in the post-test. A group of 8 virtual cars adopting DD required less space on the road to follow the drivers that took the DI course.

Modeling congestion considering sequential coupling applications: A network-cell-based method

Sequential coupling of applications is the major cause of traffic congestion and low application quality. Modeling traffic congestion under sequential coupling applications is the primary means to explore congestion mechanism, which can further support application design and adjustment to improve application quality. Existing congestion models concentrate more on traffic flow modeling based on network components, with little consideration of the influence of network application and its coupling. This paper proposes a network-cell-based congestion model for describing dynamics of congestion propagation under sequential coupling multi-applications. First, the basic characteristics of network applications are analyzed, and network applications are abstracted into network cells as functional units, which is specifically described from three perspectives: Structure, function and connection. The dynamic process of network can be modeled as intracellular reaction (single application function behavior) and intercellular interaction (coupling behavior of multi-applications). Furthermore, a network-cell-based metric to evaluate application quality is presented, and the implementation algorithm of the model is also given. Numerical simulations are implemented with comparison of typical information flow model to verify the model. Moreover, the proposed model is applied to Chengdu Metro system case to show the applicability. Furthermore, the influence of sequential coupling on congestion is further investigated, and the results show that the larger coupling strength corresponds to less congestion in peak period. This study provides guidance for application design and management to improve application quality of transportation networks.

Noisy beeping networks

Beeping networks consist of exceedingly simple computational devices whose communication is based on beeps and silence. In this work, we introduce noisy beeping networks, where the observed communication is noisy with some fixed probability of error.We show how to transform any algorithm over a noiseless beeping network into a noise-resilient version while incurring a multiplicative overhead of essentially O(log⁡n) in its round complexity, with high probability. Our coding is optimal for some (short) tasks, such as the node-coloring of cliques. Interestingly, in the case of coloring, our technique achieves the same complexity as the standard beeping model while being noise resilient.We further show how to simulate a large family of algorithms designed for distributed networks in the CONGEST(B) model over a noisy beeping network, with a multiplicative overhead of O(B⋅Δ⋅min⁡(n,Δ2)) in the round complexity, where Δ is the maximum degree of the network.

Prioritization vs. congestion on platforms: evidence from Amazon's Twitch.tv

AbstractThis article studies the efficient use of prioritizing certain content over others in Amazon's Twitch.tv, a live streaming service, taking into account the trade‐off between entry and congestion. I specify and estimate supply and demand models for live video, and a congestion model. Using technological shocks, I identify congestion costs for content providers and their consumers. Using shocks in prioritization, I identify its benefits. With estimated preferences and technological parameters, I construct counterfactuals. Without congestion, demand doubles. A supply‐side Pigouvian tax on traffic is preferred to a demand‐side one. Without prioritization, consumer welfare drops by 10%.

An Intelligent Congestion Control Strategy in Heterogeneous V2X Based on Deep Reinforcement Learning

High mobility and the complexity of mobile behavior are the main characteristics of nodes in Vehicle to Everything (V2X). Furthermore, these characteristics entail that resource deployment cannot effectively meet the demands of users for differentiated service quality. Due to this significance, the main objective of this study is to propose an intelligent congestion control strategy based on deep reinforcement learning (ICCDRL) in heterogeneous V2X, which can meet the diverse service needs of vehicles to some extent, so as to solve the problem of network congestion effectively. The proposal is implemented through three aspects: Firstly, the paper establishes a congestion control model based on DRL. Secondly, a large amount of QoS data is used as the training set to optimize the model. Finally, the congestion sensitivity factor is used to select the size of the congestion window for the next moment, resulting in an intelligent congestion control strategy based on QoS on-demand drive. For verification, a series of simulation experiments are designed on the ns-3 simulation platform. The results show that the proposed ICCDRL outperforms the traditional algorithm in terms of throughput, convergence, friendliness and fairness, and can effectively guarantee real-time, reliable information interaction in V2X.

Mitigating traffic congestion induced by transportation network companies: A policy analysis

This paper analyzes and evaluates several policies aiming to mitigate the congestion effect a Transportation Network Company (TNC) brings to bear on an idealized city that contains a dense central core surrounded by a larger periphery. The TNC offers both solo and pooling e-hail services to the users of public transport. We develop a spatial market equilibrium model over two building blocks: an aggregate congestion model that describes the traffic impact of TNC operations on all travelers in the city, including private motorists, and a matching model that estimates the TNC’s level of service based on the interactions between riders and TNC drivers. Based on the equilibrium model, we formulate and solve the optimal pricing problem, in which the TNC seeks to optimize its profit or social welfare subject to regulatory costs and/or constraints. Three congestion mitigation policies are implemented in this study: (i) a trip-based policy that charges a congestion fee on each solo trip starting or ending in the city center; (ii) a cordon-based policy that charges TNC vehicles entering the city center with zero or one passenger; and (iii) a cruising cap policy that requires the TNC to maintain the fleet utilization ratio in the city center above a threshold. Based on a case study of Chicago, we find TNC operations may have a significant congestion effect. Failing to anticipate this effect in the pricing problem leads to sub-optimal decisions that worsen traffic congestion and hurt the TNC’s profitability. Of the three policies, the trip-based policy delivers the best performance. It reduces traffic congestion modestly, keeps the TNC’s level of service almost intact, and improves overall social welfare substantially. The cruising cap policy benefits private motorists, thanks to the extra congestion relief it brings about. However, because other stakeholders together suffer a much greater loss, its net impact on social welfare is negative. Paradoxically, the policy could worsen the very traffic conditions in the city center that it is designed to improve.